Synergistic inter-clonal cooperation involving crosstalk, co-option and co-dependency can enhance the invasiveness of genetically distant cancer clones
Bibliographic record
Abstract
Abstract Background Despite intensive research, cancer remains a major health problem. The difficulties in treating cancer are due to the complex nature of this disease, including high levels of heterogeneity within tumours. Intra-tumour heterogeneity creates the conditions for inter-clonal competition and selection, which should result in selective sweeps and a reduction in levels of heterogeneity. However, in addition to competing, cancer clones could also cooperate with each other, and the positive effects of these interactions on the fitness of clones can actually contribute to maintaining the heterogeneity of tumours. Consequently, understanding the evolutionary mechanisms and pathways involved in such behaviours is of great significance for cancer treatment. This is particularly relevant for metastasis, which is the most lethal phase during cancer progression. To explore if and how genetically distant clones can cooperate during invasion, this study used three genetically distant cancer cell lines with different metastatic potentials. Results We found that (i) the conditioned media from the invasive lines increased the migration and invasion potential of the poorly metastatic line, and (ii) this inter-clonal interaction involved the TGF-β1 signalling pathway. Furthermore, when a highly and poorly metastatic lines were co-cultured, the invasive potential of both lines was enhanced, and this outcome was dependent on the co-option of the less aggressive clone into expressing a malignant phenotype. Based on our findings, we propose a two-tier model whereby highly metastatic clones can co-opt (through autocrine-paracrine crosstalk) weakly metastatic clones into expressing an invasive phenotype, which in turn augments the invasion ability of the former (i.e., a “help me help you” strategy). Conclusions We suggest that such synergistic cooperative interactions can easily emerge via crosstalk involving metastatic clones able to constitutively secrete molecules that induce and maintain their own malignant state (producer-responder clones) and clones that have the ability to respond to those signals (responder clones) and express a synergistic metastatic behaviour, regardless of the degree of overall genetic/genealogical relatedness. Taking into account the lack of therapies that directly affect the metastatic process, interfering with such cooperative behaviours that tumour cells engage in during the early steps in the metastatic cascade could provide additional strategies to increase patient survival.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".